Evidence suggests the reason is that people approach this problem using assignment inference, a process that considers all colors and concepts in the scope of the encoding system [1]}. Assignment inference is analogous to solving an assignment problem in optimization [2]}. In Fig. REF A, the scope of the encoding system includes trash and paper, even though paper was not relevant on this particular trial. Assignment inference does not simply assign a color to the concept with the strongest merit (for now, think of merit as direct association strength). Instead, the process selects the combination of color-concept pairs that maximizes total merit across all pairings. The total merit for the T-purple/P-white assignment is greater than the alternative, T-white/P-purple. Thus, observers infer that trash maps to purple, despite trash being more strongly associated with white.
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